def start():
serverData = SocketServer()
EW_videoCapture = cv2.VideoCapture(paths.EW_VIDEO_PATH)
NS_videoCapture = cv2.VideoCapture(paths.NS_VIDEO_PATH)
bgSubtractor = cv2.createBackgroundSubtractorMOG2(varThreshold=230,
detectShadows=True)
# frameWidth = int(videoCapture.get(3))
# frameHeight = int(videoCapture.get(4))
# linePoint1 = (0, int(frameHeight / 2))
# linePoint2 = (frameWidth, int(frameHeight / 2))
while True:
_, EW_frame = EW_videoCapture.read()
_, NS_frame = EW_videoCapture.read()
# cv2.line(frame, linePoint1, linePoint2, (0, 0, 255), 2)
EW_fgMask = bgSubtractor.apply(EW_frame)
NS_fgMask = bgSubtractor.apply(NS_frame)
EW_fgMask = mask_preproscessing(EW_fgMask)
NS_fgMask = mask_preproscessing(NS_fgMask)
EW_contours, _ = cv2.findContours(EW_fgMask, cv2.RETR_LIST,
cv2.CHAIN_APPROX_SIMPLE)
NS_contours, _ = cv2.findContours(NS_fgMask, cv2.RETR_LIST,
cv2.CHAIN_APPROX_SIMPLE)
serverDataStr = str(len(NS_contours)) + "+" + str(len(EW_contours))
print(serverDataStr)
serverData.send(serverDataStr)
cv2.drawContours(EW_frame, EW_contours, -1, (0, 255, 0), 2)
cv2.drawContours(NS_frame, NS_contours, -1, (0, 255, 0), 2)
cv2.imshow("EW_Contours", EW_frame)
cv2.imshow("NS_Contours", NS_frame)
key = cv2.waitKey(50)
if key == 27:
break
EW_videoCapture.release()
NS_videoCapture.release()
cv2.destroyAllWindows()
def __init__(self):
SocketServer.__init__(self)
self.BATCH_SIZE=16
self.raw_data=Loader('..//Database//Plastics_and_Chemicals_Macro.csv')
self.data,self._min,self._max=Normalize(self.raw_data)
self._data=self.data[:,14:30]
self.data=self.data[:,14:30]
self.data=torch.Tensor(self.data)
self.dataSize=self.data.shape[0]
self._dataset=Data.TensorDataset(self.data,self.data)
self.test_loader=Data.DataLoader(dataset=self._dataset,batch_size=1,shuffle=False)
self.train_loader=Data.DataLoader(dataset=self._dataset,batch_size=self.BATCH_SIZE,shuffle=True)
self.AE=self.LoadAE()
self.la,self.re=self.ModelEval(self.AE)
def __init__(self, *args, **kwargs):
"""
Crating a server object whit default host and port and set timeout 0.1 second.
:param args:
:param kwargs:
"""
super(TestSocketServer, self).__init__(*args, **kwargs)
self.server = SocketServer(timeout=0.1)
class TestSocketServer(unittest.TestCase):
"""
SocketServer unittest class.
"""
def __init__(self, *args, **kwargs):
"""
Crating a server object whit default host and port and set timeout 0.1 second.
:param args:
:param kwargs:
"""
super(TestSocketServer, self).__init__(*args, **kwargs)
self.server = SocketServer(timeout=0.1)
def testHost(self):
"""
Test host string.
:return:
"""
self.assertEqual(self.server.getHost(), prop.HOST)
def testPort(self):
"""
Test port number.
:return:
"""
self.assertEqual(self.server.getPort(), prop.PORT)
def testRunServer(self):
"""
Test server run method and timeout.
:return:
"""
try:
self.server.run()
except socket.error as error:
self.assertTrue(False, str(error))
self.assertFalse(self.server.isRunning())
import cv2
import numpy as np
import paths
from Server import SocketServer
import constants
import time, threading
serverData = SocketServer()
serverDataStr = ""
def send_periodicly():
if serverDataStr != "":
serverData.send(serverDataStr)
print("send: " + serverDataStr)
threading.Timer(10, send_periodicly).start()
def mask_preproscessing(img):
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2, 2))
# Fill any small holes
closing = cv2.morphologyEx(img, cv2.MORPH_CLOSE, kernel, iterations=1)
# Remove noise
opening = cv2.morphologyEx(closing, cv2.MORPH_OPEN, kernel, iterations=1)
# Dilate to merge adjacent blobs
dilation = cv2.dilate(opening, kernel, iterations=2)